Updated Review Available
This expert summary is for the non peer-reviewed preprint. We also summarized this paper after it underwent peer-review and was published in Nature on June 8, 2020. You can find our updated review of the published article here.
Study population and setting
A semi-mechanistic Bayesian hierarchical model was fit to observed COVID-19 deaths in 11 European countries. The model estimated the impact of large-scale non-pharmaceutical interventions on the reproductive rate of the virus, with particular attention to whether reproductive number had been driven below 1, a level at which the outbreak would die out, and on the number of infections and deaths in these countries up to March, 31, 2020.
Summary of Main Findings
59,000 deaths (95% credible interval: 21,000 – 120,000) are estimated to have been averted by non-pharmaceutical interventions in 11 European countries up to March 31, and the reproductive number of the virus is estimated to have been reduced from 3.87 to 1.43 (averaged across countries). Many times more people are estimated to have been infected by SARS-CoV-2 than have been confirmed, with estimates of attack rate ranging from 0.41% (0.09%-3.2%) in Norway to 9.8% (3.2%-26%) in Italy. Lockdown was estimated to have the greatest impact, followed by school closure, but no intervention impacts were statistically significantly different from one another.
The model is fit to observed deaths, which are likely to be more reliable than case counts or hospitalizations. The model reproduces observed data up to March 28th very well. Uncertainty from various sources is appropriately handled by the model explicitly and by the discussion implicitly. Prior distributions and parameter values are chosen based on current, best available data.
There is considerable uncertainty over model parameters such as the infection fatality ratio. Interventions are assumed to have the same impact across countries and time; the timing of country-specific interventions makes it difficult to distinguish between the effects of specific interventions. The interval between infection and death means that effects of control measures are not yet as apparent in countries in an earlier phase of the epidemic; relatedly, the model is heavily influenced by countries with a high number of deaths that implemented interventions earlier. The model assumes that If there had been no intervention, the reproductive number would not have changed, which is unlikely as people often change behavior during large outbreaks, even if no formal policies are put into place.
This study is the most thorough model-based estimate of the impact of European country-wide non-pharmaceutical interventions at the time of review.